One of the following:
class BetaFunctionTool: …

Defines a function in your own code the model can choose to call. Learn more about function calling.

name: str

The name of the function to call.

parameters: Optional[Dict[str, object]]

A JSON schema object describing the parameters of the function.

strict: Optional[bool]

Whether strict parameter validation is enforced for this function tool.

type: Literal["function"]

The type of the function tool. Always function.

allowed_callers: Optional[List[Literal["direct", "programmatic"]]]

The tool invocation context(s).

One of the following:
"direct"
"programmatic"
async_: Optional[bool]
defer_loading: Optional[bool]

Whether this function is deferred and loaded via tool search.

description: Optional[str]

A description of the function. Used by the model to determine whether or not to call the function.

output_schema: Optional[Dict[str, object]]

A JSON schema object describing the JSON value encoded in string outputs for this function.

class BetaFileSearchTool: …

A tool that searches for relevant content from uploaded files. Learn more about the file search tool.

type: Literal["file_search"]

The type of the file search tool. Always file_search.

vector_store_ids: List[str]

The IDs of the vector stores to search.

filters: Optional[Filters]

A filter to apply.

One of the following:
class FiltersComparisonFilter: …

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: str

The key to compare against the value.

type: Literal["eq", "ne", "gt", 5 more]

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

  • eq: equals
  • ne: not equal
  • gt: greater than
  • gte: greater than or equal
  • lt: less than
  • lte: less than or equal
  • in: in
  • nin: not in
One of the following:
"eq"
"ne"
"gt"
"gte"
"lt"
"lte"
"in"
"nin"
value: Union[str, float, bool, List[Union[str, float]]]

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:
str
float
bool
List[Union[str, float]]
One of the following:
str
float
class FiltersCompoundFilter: …

Combine multiple filters using and or or.

filters: List[FiltersCompoundFilterFilter]

Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.

One of the following:
class FiltersCompoundFilterFilterComparisonFilter: …

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: str

The key to compare against the value.

type: Literal["eq", "ne", "gt", 5 more]

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

  • eq: equals
  • ne: not equal
  • gt: greater than
  • gte: greater than or equal
  • lt: less than
  • lte: less than or equal
  • in: in
  • nin: not in
One of the following:
"eq"
"ne"
"gt"
"gte"
"lt"
"lte"
"in"
"nin"
value: Union[str, float, bool, List[Union[str, float]]]

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:
str
float
bool
List[Union[str, float]]
One of the following:
str
float
object
type: Literal["and", "or"]

Type of operation: and or or.

One of the following:
"and"
"or"
max_num_results: Optional[int]

The maximum number of results to return. This number should be between 1 and 50 inclusive.

ranking_options: Optional[RankingOptions]

Ranking options for search.

text_weight: float

The weight of the text in the reciprocal ranking fusion.

ranker: Optional[Literal["auto", "default-2024-11-15"]]

The ranker to use for the file search.

One of the following:
"auto"
"default-2024-11-15"
score_threshold: Optional[float]

The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will attempt to return only the most relevant results, but may return fewer results.

class BetaComputerTool: …

A tool that controls a virtual computer. Learn more about the computer tool.

type: Literal["computer"]

The type of the computer tool. Always computer.

class BetaComputerUsePreviewTool: …

A tool that controls a virtual computer. Learn more about the computer tool.

display_height: int

The height of the computer display.

display_width: int

The width of the computer display.

environment: Literal["windows", "mac", "linux", 2 more]

The type of computer environment to control.

One of the following:
"windows"
"mac"
"linux"
"ubuntu"
"browser"
type: Literal["computer_use_preview"]

The type of the computer use tool. Always computer_use_preview.

class BetaWebSearchTool: …

Search the Internet for sources related to the prompt. Learn more about the web search tool.

type: Literal["web_search", "web_search_2025_08_26"]

The type of the web search tool. One of web_search or web_search_2025_08_26.

One of the following:
"web_search"
"web_search_2025_08_26"
external_web_access: Optional[bool]

Allow live internet access for web search. Defaults to true when omitted. When false, the web search tool runs in offline/cache-only mode and will not fetch new external content.

filters: Optional[Filters]

Filters for the search.

allowed_domains: Optional[List[str]]

Allowed domains for the search. If not provided, all domains are allowed. Subdomains of the provided domains are allowed as well.

Example: ["pubmed.ncbi.nlm.nih.gov"]

search_context_size: Optional[Literal["low", "medium", "high"]]

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:
"low"
"medium"
"high"
user_location: Optional[UserLocation]

The approximate location of the user.

city: Optional[str]

Free text input for the city of the user, e.g. San Francisco.

country: Optional[str]

The two-letter ISO country code of the user, e.g. US.

region: Optional[str]

Free text input for the region of the user, e.g. California.

timezone: Optional[str]

The IANA timezone of the user, e.g. America/Los_Angeles.

type: Optional[Literal["approximate"]]

The type of location approximation. Always approximate.

class Mcp: …

Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

server_label: str

A label for this MCP server, used to identify it in tool calls.

type: Literal["mcp"]

The type of the MCP tool. Always mcp.

allowed_callers: Optional[List[Literal["direct", "programmatic"]]]

The tool invocation context(s).

One of the following:
"direct"
"programmatic"
allowed_tools: Optional[McpAllowedTools]

List of allowed tool names or a filter object.

One of the following:
List[str]

A string array of allowed tool names

class McpAllowedToolsMcpToolFilter: …

A filter object to specify which tools are allowed.

read_only: Optional[bool]

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: Optional[List[str]]

List of allowed tool names.

authorization: Optional[str]

An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

Deprecatedconnector_id: Optional[Literal["connector_dropbox", "connector_gmail", "connector_googlecalendar", 5 more]]

Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

This field is deprecated for models released after September 1, 2026. Use server_url to connect to a remote MCP server, or tunnel_id to connect through a Secure MCP Tunnel.

Currently supported connector_id values are:

  • Dropbox: connector_dropbox
  • Gmail: connector_gmail
  • Google Calendar: connector_googlecalendar
  • Google Drive: connector_googledrive
  • Microsoft Teams: connector_microsoftteams
  • Outlook Calendar: connector_outlookcalendar
  • Outlook Email: connector_outlookemail
  • SharePoint: connector_sharepoint
One of the following:
"connector_dropbox"
"connector_gmail"
"connector_googlecalendar"
"connector_googledrive"
"connector_microsoftteams"
"connector_outlookcalendar"
"connector_outlookemail"
"connector_sharepoint"
defer_loading: Optional[bool]

Whether this MCP tool is deferred and discovered via tool search.

headers: Optional[Dict[str, str]]

Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

require_approval: Optional[McpRequireApproval]

Specify which of the MCP server’s tools require approval.

One of the following:
class McpRequireApprovalMcpToolApprovalFilter: …

Specify which of the MCP server’s tools require approval. Can be always, never, or a filter object associated with tools that require approval.

always: Optional[McpRequireApprovalMcpToolApprovalFilterAlways]

A filter object to specify which tools are allowed.

read_only: Optional[bool]

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: Optional[List[str]]

List of allowed tool names.

never: Optional[McpRequireApprovalMcpToolApprovalFilterNever]

A filter object to specify which tools are allowed.

read_only: Optional[bool]

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: Optional[List[str]]

List of allowed tool names.

Literal["always", "never"]

Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

One of the following:
"always"
"never"
server_description: Optional[str]

Optional description of the MCP server, used to provide more context.

server_url: Optional[str]

The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

formaturi
tunnel_id: Optional[str]

The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

class CodeInterpreter: …

A tool that runs Python code to help generate a response to a prompt.

container: CodeInterpreterContainer

The code interpreter container. Can be a container ID or an object that specifies uploaded file IDs to make available to your code, along with an optional memory_limit setting.

One of the following:
str

The container ID.

class CodeInterpreterContainerCodeInterpreterToolAuto: …

Configuration for a code interpreter container. Optionally specify the IDs of the files to run the code on.

type: Literal["auto"]

Always auto.

file_ids: Optional[List[str]]

An optional list of uploaded files to make available to your code.

memory_limit: Optional[Literal["1g", "4g", "16g", "64g"]]

The memory limit for the code interpreter container.

One of the following:
"1g"
"4g"
"16g"
"64g"
network_policy: Optional[CodeInterpreterContainerCodeInterpreterToolAutoNetworkPolicy]

Network access policy for the container.

One of the following:
class BetaContainerNetworkPolicyDisabled: …
type: Literal["disabled"]

Disable outbound network access. Always disabled.

class BetaContainerNetworkPolicyAllowlist: …
allowed_domains: List[str]

A list of allowed domains when type is allowlist.

type: Literal["allowlist"]

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: Optional[List[BetaContainerNetworkPolicyDomainSecret]]

Optional domain-scoped secrets for allowlisted domains.

domain: str

The domain associated with the secret.

minLength1
name: str

The name of the secret to inject for the domain.

minLength1
value: str

The secret value to inject for the domain.

minLength1
maxLength10485760
type: Literal["code_interpreter"]

The type of the code interpreter tool. Always code_interpreter.

allowed_callers: Optional[List[Literal["direct", "programmatic"]]]

The tool invocation context(s).

One of the following:
"direct"
"programmatic"
class ProgrammaticToolCalling: …
type: Literal["programmatic_tool_calling"]

The type of the tool. Always programmatic_tool_calling.

class ImageGeneration: …

A tool that generates images using the GPT image models.

type: Literal["image_generation"]

The type of the image generation tool. Always image_generation.

action: Optional[Literal["generate", "edit", "auto"]]

Whether to generate a new image or edit an existing image. Default: auto.

One of the following:
"generate"
"edit"
"auto"
background: Optional[Literal["transparent", "opaque", "auto"]]

Allows to set transparency for the background of the generated image(s). Must be one of transparent, opaque, or auto (default value). When auto is used, the model will automatically determine the best background for the image.

gpt-image-2.5-sunburst and gpt-image-2.5-flare, including their 2026-09-08 snapshots, support opaque and transparent backgrounds. Transparent backgrounds are available for supported GPT Image models. For gpt-image-2 and gpt-image-2-2026-04-21, this support is in preview. When using transparent, set the output format to png or webp.

One of the following:
"transparent"
"opaque"
"auto"
input_fidelity: Optional[Literal["high", "low"]]

Controls fidelity to the original input image(s). This parameter is supported for GPT image models that support input fidelity. gpt-image-2 and gpt-image-2-2026-04-21 ignore this parameter.

One of the following:
"high"
"low"
input_image_mask: Optional[ImageGenerationInputImageMask]

Optional mask for inpainting. Contains image_url (string, optional) and file_id (string, optional).

file_id: Optional[str]

File ID for the mask image.

image_url: Optional[str]

Base64-encoded mask image.

model: Optional[Union[str, Literal["gpt-image-1", "gpt-image-1-mini", "gpt-image-2", 7 more], null]]

The image generation model to use. One of gpt-image-1, gpt-image-1-mini, gpt-image-1.5, gpt-image-2, gpt-image-2-2026-04-21, gpt-image-2.5-sunburst, gpt-image-2.5-sunburst-2026-09-08, gpt-image-2.5-flare, gpt-image-2.5-flare-2026-09-08, or chatgpt-image-latest. Default: gpt-image-1.

One of the following:
str
Literal["gpt-image-1", "gpt-image-1-mini", "gpt-image-2", 7 more]

The image generation model to use. One of gpt-image-1, gpt-image-1-mini, gpt-image-1.5, gpt-image-2, gpt-image-2-2026-04-21, gpt-image-2.5-sunburst, gpt-image-2.5-sunburst-2026-09-08, gpt-image-2.5-flare, gpt-image-2.5-flare-2026-09-08, or chatgpt-image-latest. Default: gpt-image-1.

One of the following:
"gpt-image-1"
"gpt-image-1-mini"
"gpt-image-2"
"gpt-image-2-2026-04-21"
"gpt-image-2.5-sunburst"
"gpt-image-2.5-sunburst-2026-09-08"
"gpt-image-2.5-flare"
"gpt-image-2.5-flare-2026-09-08"
"gpt-image-1.5"
"chatgpt-image-latest"
moderation: Optional[Literal["auto", "low"]]

Moderation level for the generated image. Default: auto.

One of the following:
"auto"
"low"
output_compression: Optional[int]

Compression level for the output image. Default: 100.

minimum0
maximum100
output_format: Optional[Literal["png", "webp", "jpeg"]]

The output format of the generated image. One of png, webp, or jpeg. Default: png.

One of the following:
"png"
"webp"
"jpeg"
partial_images: Optional[int]

Number of partial images to generate in streaming mode, from 0 (default value) to 3.

minimum0
maximum3
quality: Optional[Literal["low", "medium", "high", 3 more]]

The quality of the generated image. The GPT image models support low, medium, and high. gpt-image-2.5-sunburst and gpt-image-2.5-flare, including their 2026-09-08 snapshots, also support xhigh and max. Default: auto.

One of the following:
"low"
"medium"
"high"
"xhigh"
"max"
"auto"
size: Optional[Union[str, Literal["1024x1024", "1024x1536", "1536x1024", "auto"], null]]

The size of the generated images. For gpt-image-2, gpt-image-2-2026-04-21, gpt-image-2.5-sunburst, gpt-image-2.5-sunburst-2026-09-08, gpt-image-2.5-flare, and gpt-image-2.5-flare-2026-09-08, arbitrary resolutions are supported as WIDTHxHEIGHT strings, for example 1536x864. Width and height must both be divisible by 16 and the requested aspect ratio must be between 1:3 and 3:1. Resolutions above 2560x1440 are experimental, and the maximum supported resolution is 3840x2160. The requested size must also satisfy the model’s current pixel and edge limits. The standard sizes 1024x1024, 1536x1024, and 1024x1536 are supported by the GPT image models; auto is supported for models that allow automatic sizing. For dall-e-2, use one of 256x256, 512x512, or 1024x1024. For dall-e-3, use one of 1024x1024, 1792x1024, or 1024x1792.

One of the following:
str
Literal["1024x1024", "1024x1536", "1536x1024", "auto"]

The size of the generated images. For gpt-image-2, gpt-image-2-2026-04-21, gpt-image-2.5-sunburst, gpt-image-2.5-sunburst-2026-09-08, gpt-image-2.5-flare, and gpt-image-2.5-flare-2026-09-08, arbitrary resolutions are supported as WIDTHxHEIGHT strings, for example 1536x864. Width and height must both be divisible by 16 and the requested aspect ratio must be between 1:3 and 3:1. Resolutions above 2560x1440 are experimental, and the maximum supported resolution is 3840x2160. The requested size must also satisfy the model’s current pixel and edge limits. The standard sizes 1024x1024, 1536x1024, and 1024x1536 are supported by the GPT image models; auto is supported for models that allow automatic sizing. For dall-e-2, use one of 256x256, 512x512, or 1024x1024. For dall-e-3, use one of 1024x1024, 1792x1024, or 1024x1792.

One of the following:
"1024x1024"
"1024x1536"
"1536x1024"
"auto"
class LocalShell: …

A tool that allows the model to execute shell commands in a local environment.

type: Literal["local_shell"]

The type of the local shell tool. Always local_shell.

class BetaFunctionShellTool: …

A tool that allows the model to execute shell commands.

type: Literal["shell"]

The type of the shell tool. Always shell.

allowed_callers: Optional[List[Literal["direct", "programmatic"]]]

The tool invocation context(s).

One of the following:
"direct"
"programmatic"
environment: Optional[Environment]
One of the following:
class BetaContainerAuto: …
type: Literal["container_auto"]

Automatically creates a container for this request

file_ids: Optional[List[str]]

An optional list of uploaded files to make available to your code.

memory_limit: Optional[Literal["1g", "4g", "16g", "64g"]]

The memory limit for the container.

One of the following:
"1g"
"4g"
"16g"
"64g"
network_policy: Optional[NetworkPolicy]

Network access policy for the container.

One of the following:
class BetaContainerNetworkPolicyDisabled: …
type: Literal["disabled"]

Disable outbound network access. Always disabled.

class BetaContainerNetworkPolicyAllowlist: …
allowed_domains: List[str]

A list of allowed domains when type is allowlist.

type: Literal["allowlist"]

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: Optional[List[BetaContainerNetworkPolicyDomainSecret]]

Optional domain-scoped secrets for allowlisted domains.

domain: str

The domain associated with the secret.

minLength1
name: str

The name of the secret to inject for the domain.

minLength1
value: str

The secret value to inject for the domain.

minLength1
maxLength10485760
skills: Optional[List[Skill]]

An optional list of skills referenced by id or inline data.

One of the following:
class BetaSkillReference: …
skill_id: str

The ID of the referenced skill.

minLength1
maxLength64
type: Literal["skill_reference"]

References a skill created with the /v1/skills endpoint.

version: Optional[str]

Optional skill version. Use a positive integer or ‘latest’. Omit for default.

class BetaInlineSkill: …
description: str

The description of the skill.

name: str

The name of the skill.

source: BetaInlineSkillSource

Inline skill payload

data: str

Base64-encoded skill zip bundle.

minLength1
maxLength70254592
media_type: Literal["application/zip"]

The media type of the inline skill payload. Must be application/zip.

type: Literal["base64"]

The type of the inline skill source. Must be base64.

type: Literal["inline"]

Defines an inline skill for this request.

class BetaLocalEnvironment: …
type: Literal["local"]

Use a local computer environment.

skills: Optional[List[BetaLocalSkill]]

An optional list of skills.

description: str

The description of the skill.

name: str

The name of the skill.

path: str

The path to the directory containing the skill.

class BetaContainerReference: …
container_id: str

The ID of the referenced container.

type: Literal["container_reference"]

References a container created with the /v1/containers endpoint

class BetaCustomTool: …

A custom tool that processes input using a specified format. Learn more about custom tools

name: str

The name of the custom tool, used to identify it in tool calls.

type: Literal["custom"]

The type of the custom tool. Always custom.

allowed_callers: Optional[List[Literal["direct", "programmatic"]]]

The tool invocation context(s).

One of the following:
"direct"
"programmatic"
async_: Optional[bool]

Whether the tool response can be returned asynchronously versus immediately returned on next response creation.

defer_loading: Optional[bool]

Whether this tool should be deferred and discovered via tool search.

description: Optional[str]

Optional description of the custom tool, used to provide more context.

format: Optional[Format]

The input format for the custom tool. Default is unconstrained text.

One of the following:
class FormatText: …

Unconstrained free-form text.

type: Literal["text"]

Unconstrained text format. Always text.

class FormatGrammar: …

A grammar defined by the user.

definition: str

The grammar definition.

syntax: Literal["lark", "regex"]

The syntax of the grammar definition. One of lark or regex.

One of the following:
"lark"
"regex"
type: Literal["grammar"]

Grammar format. Always grammar.

class BetaNamespaceTool: …

Groups function/custom tools under a shared namespace.

description: str

A description of the namespace shown to the model.

name: str

The namespace name used in tool calls (for example, crm).

minLength1
tools: List[Tool]

The function/custom tools available inside this namespace.

One of the following:
class ToolFunction: …
name: str
minLength1
maxLength128
type: Literal["function"]
allowed_callers: Optional[List[Literal["direct", "programmatic"]]]

The tool invocation context(s).

One of the following:
"direct"
"programmatic"
async_: Optional[bool]

Whether the tool response can be returned asynchronously versus immediately returned on next response creation.

defer_loading: Optional[bool]

Whether this function should be deferred and discovered via tool search.

description: Optional[str]
output_schema: Optional[Dict[str, object]]

A JSON Schema describing the JSON value encoded in string outputs for this function tool. This does not describe content-array outputs.

parameters: Optional[object]
strict: Optional[bool]

Whether to enforce strict parameter validation. If omitted, Responses attempts to use strict validation when the schema is compatible, and falls back to non-strict validation otherwise.

class BetaCustomTool: …

A custom tool that processes input using a specified format. Learn more about custom tools

name: str

The name of the custom tool, used to identify it in tool calls.

type: Literal["custom"]

The type of the custom tool. Always custom.

allowed_callers: Optional[List[Literal["direct", "programmatic"]]]

The tool invocation context(s).

One of the following:
"direct"
"programmatic"
async_: Optional[bool]

Whether the tool response can be returned asynchronously versus immediately returned on next response creation.

defer_loading: Optional[bool]

Whether this tool should be deferred and discovered via tool search.

description: Optional[str]

Optional description of the custom tool, used to provide more context.

format: Optional[Format]

The input format for the custom tool. Default is unconstrained text.

One of the following:
class FormatText: …

Unconstrained free-form text.

type: Literal["text"]

Unconstrained text format. Always text.

class FormatGrammar: …

A grammar defined by the user.

definition: str

The grammar definition.

syntax: Literal["lark", "regex"]

The syntax of the grammar definition. One of lark or regex.

One of the following:
"lark"
"regex"
type: Literal["grammar"]

Grammar format. Always grammar.

type: Literal["namespace"]

The type of the tool. Always namespace.

class BetaToolSearchTool: …

Hosted or BYOT tool search configuration for deferred tools.

type: Literal["tool_search"]

The type of the tool. Always tool_search.

description: Optional[str]

Description shown to the model for a client-executed tool search tool.

execution: Optional[Literal["server", "client"]]

Whether tool search is executed by the server or by the client.

One of the following:
"server"
"client"
parameters: Optional[object]

Parameter schema for a client-executed tool search tool.

class BetaWebSearchPreviewTool: …

This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

type: Literal["web_search_preview", "web_search_preview_2025_03_11"]

The type of the web search tool. One of web_search_preview or web_search_preview_2025_03_11.

One of the following:
"web_search_preview"
"web_search_preview_2025_03_11"
search_content_types: Optional[List[Literal["text", "image"]]]
One of the following:
"text"
"image"
search_context_size: Optional[Literal["low", "medium", "high"]]

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:
"low"
"medium"
"high"
user_location: Optional[UserLocation]

The user’s location.

type: Literal["approximate"]

The type of location approximation. Always approximate.

city: Optional[str]

Free text input for the city of the user, e.g. San Francisco.

country: Optional[str]

The two-letter ISO country code of the user, e.g. US.

region: Optional[str]

Free text input for the region of the user, e.g. California.

timezone: Optional[str]

The IANA timezone of the user, e.g. America/Los_Angeles.

class BetaApplyPatchTool: …

Allows the assistant to create, delete, or update files using unified diffs.

type: Literal["apply_patch"]

The type of the tool. Always apply_patch.

allowed_callers: Optional[List[Literal["direct", "programmatic"]]]

The tool invocation context(s).

One of the following:
"direct"
"programmatic"